Deeplead

Find a person's phone number by LinkedIn URL, email, or full name and company domain

persons_find_phone

Find a person's phone number by LinkedIn URL, email, or full name and company domain. Covers professional contacts only: people in their role at a company, not private individuals. Charges 2 credits only when a phone number is found.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "persons_find_phone"
  }
}

Input Schema

Name	Required	Description
`name`	No	Full name, e.g. "Jane Doe"; needs domain
`email`	No	Known email address identifying the person
`domain`	No	Company domain, e.g. "acme.com"
`linkedin`	No	e.g. "https://www.linkedin.com/in/jane-doe"

Output Schema

Name	Required	Description	Default
`name`	Yes
`found`	Yes
`phone`	Yes
`phones`	Yes
`jobTitle`	Yes
`linkedin`	Yes
`companyName`	Yes
`chargedCredits`	Yes
`companyWebsite`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 26, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses the billing rule ('charges 2 credits only when a phone number is found'), which is genuine behavioral context the annotations do not carry — readOnlyHint=false alone would not tell an agent about cost or conditional charging. It does not mention rate limits or auth requirements, but the credit policy is the material trait here.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action and inputs, then the scope limit, then the cost. Every sentence carries information an agent needs; nothing is padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need no explanation, and the description covers scope, inputs, and cost. The only minor omission is what a successful result implies for follow-up (e.g. coverage/likelihood limits), but nothing essential to correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all four parameters are already documented, including the constraint that name requires a domain. The description restates the accepted input combinations but adds no format or precedence detail beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Find a person's phone number') and enumerates the three accepted lookup keys, which cleanly separates it from siblings like persons_find_email or persons_lookup. The scope qualifier ('professional contacts only') further pins down what the tool returns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-not boundary: professional/role-based contacts, not private individuals. It does not name the sibling alternative (persons_find_email) for when a phone is not the target, so the routing guidance is clear but not fully comparative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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